code: def compute_params_for_ss_release(eps, delta):
      """Computes sigma for additive Gaussian noise scaled by smooth sensitivity.
  
      Presently not used. (We proceed via RDP analysis.)
  
      Compute beta, sigma for applying Lemma 2.6 (full version of Nissim et al.) via
      Lemma 2.10.
      """
      # Rather than applying Lemma 2.10 directly, which would give suboptimal alpha,
      # (see http://www.cse.psu.edu/~ads22/pubs/NRS07/NRS07-full-draft-v1.pdf),
      # we extract a sufficient condition on alpha from its proof.
      #
      # Let a = rho_(delta/2)(Z_1). Then solve for alpha such that
      # 2 alpha a + alpha^2 = eps/2.
      a = scipy.special.ndtri(1 - delta / 2)
      alpha = math.sqrt(a**2 + eps / 2) - a
  
      beta = eps / (2 * scipy.special.chdtri(1, delta / 2))
  
      return alpha, beta
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  from absl import app
  import numpy
  import scipy
  import sympy
  import core
label_desc: Use image node_id 16 for calling a global function with example usage: compute_params_for_ss_release(eps, delta) and returns: alpha,  beta